1. Field of the Invention
The present general inventive concept relates to an apparatus to detect a homogeneous region of an image, and a method thereof. More particularly, the present general inventive concept relates to a homogeneous region detector capable of correctly detecting a homogeneous region of an image using an adaptive threshold appropriate to properties of the image, and a method thereof.
2. Description of the Related Art
Generally, a homogeneous region in an image is used for a variety of image processing fields. For example, the homogeneous region may be used for estimation of image noise since a signal-to-noise (S/N) ratio of the homogeneous region is low. Also, due to spatial redundancy of the homogeneous region, efficiency of image compression can be improved using the homogeneous region. Furthermore, when detecting scene transition of video, the homogeneous region enhances motion tolerance of frame differences. For image interpolation, an interpolation value can be obtained thorough a simple calculation in the homogeneous region, thereby saving costs. As explained above, the homogeneous region is applied to diverse fields of image processing. Therefore, correct detection of the homogeneous region is an important matter.
FIG. 1 is a view illustrating a conventional method for detecting a homogeneous region of an image. Referring to FIG. 1, a conventional homogeneous region detector 100 comprises a local region standard deviation calculation part 10 and a comparison part 20. The local region standard deviation calculation part 10 divides an input image into M×M regions and calculates the standard deviation of each region. The comparison part 20 compares the standard deviation calculated with respect to the each region to a preset fixed threshold T. A region having a smaller standard deviation than the preset fixed threshold T is determined to be a homogeneous region.
However, with the conventional detecting method using the fixed threshold, it is hard to precisely detect the homogeneous region according to an image or image noise. For example, a texture region could be detected as a homogeneous region, or a real homogeneous region could fail to be detected as the homogeneous region according to the fixed threshold. When detection of the homogeneous region is not correct, noise estimation in the detected region or other post-processing of the image cannot be effectively performed.